Predicting Labor Onset with Machine Learning

Bishop scoring method was used as the control group of this study. To evaluate the prediction ability of the control group and make the traditional Bishop evaluation method comparable with the machine learning method proposed by us, we processed the data of the control group as follows (taking a group with Bishop score of 6 as an example): The root mean square error (RMSE) was calculated from the real value of the time from induced labor to labor for each patient in this group and then the average value was taken. Then, in this group, a total of 31 mean square error values can be obtained. The groups with Bishop scores of 0, 1, 2, 3, 4, 6, and 7 could generate a total of 101 RMSE values similar to the procedure mentioned above. This processing method, which takes the mean value from induced labor to labor of each Bishop score group as the predicted value of each group, is the most fair data processing method of the control group. In addition, we also conducted experiments to fit bishop score and the time from induction of labor to labor with linear regression model.
We finally used cervical length, Bishop score, angle, age, induced labor time (ILT), measurement time (MT), the time from measurement to induced labor (MTILT), method of induced labor, and primiparity/multiparity as the input of three machine learning algorithms in the experimental group. The output of machine learning algorithm is the predicted time from induced labor to labor. The explanation of each feature is described in Table 2. Among them, the relationship between the three time variables is shown in Fig. 3. In Fig. 3, the three variables below in green are the input variables of the model, while the one above in yellow is the result that the model aims to predict, which is the output variable of the model. The induced labor time and measurement time is expressed in weeks, and the time from measurement to induced labor is expressed in days.
Table 2

Feature introduction

Feature name	Feature interpretation	Source
Cervical length	The cervical length of puerperal woman	Ultrasonic data
Bishop score	The score of Bishop method	Clinical data
Angle	Angle of the uterine wall at the cervical opening	Ultrasonic data
Age	Age of the pregnant woman	Clinical data
Induced labor time (ILT)	Induced labor time refers to the time when the doctor induces labor for pregnant women, and the unit is converted to weeks	Clinical data
Measurement time (MT)	The measurement time is the time when the doctor carries out ultrasonography on pregnant women, and the unit is converted to weeks	Clinical data
The time from measurement to induced labor (MTILT)	The time from measurement to induced labor is the time interval from ultrasonography to induction of labor, and the unit is converted into days	Clinical data
Method of induced labor	Methods of induced labor adopted by pregnant women	Clinical data
Primiparity/multiparity	Is primiparity or multiparity	Clinical data

Fig. 3

Diagram of four time variables; ILTLT The time from induction of labor to labor, MT Measurement time, MTILT Measurement time to induced labor time, ILT Induction of labor time

Method of induced labor and primiparity/multiparity are category features, which cannot be directly used as the input of the machine learning model. These two features need to be processed further. The categorical features are not numerical features but discrete sets, such as method of induced labor, that include misoprostol, oxytocin, amniotomy, Propess (PGE2), or none. When dealing with the two category features of primiparity/multiparity and method of induced labor, we used one-hot coding method to convert them into numerical characteristics. The specific process is to use two values to indicate whether the puerperal woman had a primiparity or multiparity delivery. If the value is 10, it means primiparity, and if the value is 01, it means multiparity. Five numerical values were used to represent the methods of induced labor of pregnant women. We selected three real pregnant women in the data set and showed the one-hot coding of their method of induced labor as presented in Table 3. The first Puerperal woman used one method to induce labor: oxytocin. The second Puerperal woman was induced by two methods: oxytocin and miso. The third woman was induced by three methods: misoprostol, oxytocin and amniotomy.
Table 3

One-hot coding method to convert category features into numerical value. Example explanation of one-hot coding

Methods	Misoprostol	Oxytocin	Amniotomy	Propess	None
Puerperal woman 1: oxytocin	0	1	0	0	0
Puerperal woman 2: misoprostol and oxytocin	1	1	0	0	0
Puerperal woman 3: misoprostol、oxytocin and amniotomy	1	1	1	0	0

“Methods” represent the methods of labor induction. Puerperal woman 1 only used “oxytocin”. Puerperal woman 2 used “misoprostol” and “oxytocin”. Puerperal woman 3 used “misoprostol”、 “oxytocin” and “amniotomy”